A generic support vector machine model for preoperative glioma survival associations.

Journal: Radiology
Published Date: Dec 8, 2014

Abstract

PURPOSE: To develop a generic support vector machine (SVM) model by using magnetic resonance (MR) imaging-based blood volume distribution data for preoperative glioma survival associations and to prospectively evaluate the diagnostic effectiveness of this model in autonomous patient data.

Authors

  • Kyrre E Emblem
    From the Intervention Centre (K.E.E., A.B.), Department of Radiology (P.D.T., J.K.H.), and Department of Neurosurgery (T.R.M.), Oslo University Hospital, N-0027 Sognsvannsveien 20, 0372 Oslo, Norway; Department of Radiology and Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, Mass (K.E.E., M.C.P., O.R.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (M.C.P.); Department of Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany (F.G.Z., L.R.S.); and Department of Physics, University of Oslo, Oslo, Norway (A.B.).
  • Marco C Pinho
  • Frank G Zöllner
  • Paulina Due-Tonnessen
  • John K Hald
  • Lothar R Schad
  • Torstein R Meling
  • Otto Rapalino
  • Atle Bjornerud

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